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[en] Soil-gas radon time series data has been generated at Dharamshala station for seismic studies in NW Himalayas, India. Compared with the influence of temperature and pressure, radon and rainfall have shown a strong correlation. Decomposition of radon time series into three component series (seasonal, trend, and residual) has been done for further recognizing the authentic anomalous values. The irregular patterns in daily and residual radon data have been associated with earthquake events and rainfall. This monitoring station found to be sensitive to the seismic events within a distance of about 70 km. (author)
[en] Cosmic-ray neutron sensing: from noise to a well established method for non-invasive soil moisture estimation Cosmic ray neutron sensing (CRNS) has been introduced as a new non-invasive large scale method for soil moisture estimation. It is based on the inverse relationship between natural neutrons created by cosmic-ray and the presence of hydrogen at the land-surface, which is predominantly stored as water in the soil (Zreda et al., 2012). Noteworthy, this effect was well known by physicists with studies dating back more than half a century but it was considered as a noise (Hendrick and Edge, 1966). Only several years later, the use of natural neutron fluxes measured at the ground surface for quantifying soil moisture and snow water equivalent has been presented (Kodama et al., 1979). In these experiments, however, the neutron detector was installed below ground and the signal was strongly related to the hydrogen pools close to the probe. For this reason, this set-up probably did not provide relevant advantages in comparison to other point-scale soil moisture techniques (e.g., TDR) and it was considered for monitoring only extreme snowpack conditions (Morin, et al., 2012). In contrast, Zreda et al. (2012) showed that the signal of a neutron detector installed above-ground is sensitive to soil moisture within a large footprint of hundreds of meters horizontally and a soil depth of several decimeters. In such a way, they put CRNS in a new perspective proving to be a valuable technique to estimate soil moisture at an intermediate scale and showing to be a promising method with a range of applications. Above-ground CRNS method for soil moisture estimation is now used by several research groups all around the world and several national networks have been established. Most of the applications focus on detecting temporal soil moisture dynamics but promising results have been shown also as a rover for covering larger areas, for estimation biomass, water interception and large scale snow observations.